China 6 moving average window method for real driving emission evaluation: Challenges, causes, and impacts

Investigating the impact of high-altitude on vehicle carbon emissions: A comprehensive on-road driving study

This study addresses the literature gap concerning accurately identifying vehicle carbon emission characteristics in high-altitude areas. Utilizing a portable emission measurement system (PEMS) for real-world testing, we quantified the influence of altitude on carbon emissions from light-duty gasoline (LDGV) and diesel vehicles (LDDV). The Random Forest (RF) algorithm was employed to analyze the complex nonlinear relationships between altitude, meteorological conditions, driving patterns, and carbon dioxide (CO2) emissions, enabling predictions across different altitudes. The results showed that CO2 emissions progressively increase with elevation. Furthermore, as altitude increases, combustion efficiency declines, and the overall impact of driving conditions on emission rates diminishes. Altitude and meteorological factors significantly contributed to CO2 emissions, whereas driving conditions and road grades contributed less. Compared with the COPERT model, the RF model demonstrates strong accuracy in predicting carbon emissions at different altitudes. Specifically, the CO2 emission rate nearly triples as altitude increases from 2.0 km to 4.5 km. This research bridges a critical gap in the understanding carbon emissions from high-altitude vehicles, offering insights into policy development for emission reduction strategies in such regions. Future studies should integrate diverse testing methodologies and comprehensive surveys to validate and extend the findings.

A fuel-consumption based window method for PEMS NOx emission calculation of heavy-duty diesel vehicles: Method description and case demonstration

Due to the lack of engine reference torque and the accumulated work of reference transient cycle, the work based window (WBW) method for portable emission measurement system test data processing cannot be used for vehicle emission assessment in the current on-board diagnostics (OBD) system in China. In this work, a fuel-consumption based window (FBW) method was proposed to imitate a WBW method procedure by using fuel consumption rate as an alternative parameter to scale the window so the entire procedure can be based on the attainable data items in the OBD system. Some key issues regarding converting WBW method to FBW method, including window separation, window average power ratio calculation and specific NOx emission conversion from mg/kg. fuel to mg/kW.h, were solved by linking the 100-km fuel consumption and the average vehicle specific power of China World Transient Vehicle Cycle test. The comparison between the FBW and WBW methods on the NOx emission calculation results shows that the number of all windows, the number of valid windows, and the thresholds for >50% valid windows are quite similar for WBW and FBW methods. The estimation accuracy of average power ratio for the FBW method depends on the value of transmission efficiency of vehicle driveline. The deviations of 90% specific NOx emission in mg/kW.h between the two methods are smaller than 6% for the cases investigated in the present work.